Objective To evaluate the sensitivity and optimized scanning parameter of 64-slice spiral CT in detection of pulmonary nodules with different size and density. Methods Three groups of prosthesis nodules with diameter of 2.5～13 mm and different density (soft-tissue, low density, and ground glass opacity,GGO)were taken into the chest phantom equivalent to human tissue,then scanned with Philips Brilliance 64 scanner in standard dose(tube voltage:120 kV, tube current: 250 mAs)and low-dose(tube voltage:120 kV, tube current: 50, 30,and 21mAs) respectively. The radiation dose(CTDIw and DLP) of the scans, Hounsfield unit(HU) and standard deviation(SD) of CT values in different regions of the phantom, and visibility of the nodules was assessed and recorded.Results The radiation dose of 64-slices spiral CT scanning in low-dose(tube current 21～51 mAs) decreased to 8%～20% of which scanning in standard-dose(250 mAs). There was no statistical difference between the CT values in different regions of the phantom (P>0.05), while the SD of CT values was of statistical significantce (P<0.001) and SD increased with the increment of the density under different scanning parameters. None of the nodules besides of GGO nodules with 2.5 mm and 4 mm in size scanned at 21 mAs was invisible. Conclusion GGO nodules of 2.5 mm in diameter can be detected with 64-slice spiral CT using 30 mAs at experimental study, which might be the optimized dose for detecting pulmonary nodules.

Objective To analyze the image noise and artifact of low-dose chest CT scanning and the distribution pattern. Methods A chest phantom equivalent to human tissue was scanned by 64 slices spiral scanner at standard dose (250 mAs) and low-dose (50, 30,and 21 mAs) respectively, HU in sites of the phantom and SD of which was recorded. 200 patients with pulmonary nodules were scanned at 30 or 21 mAs for minimal length. The relationship between severity of noise and artifact in chest low-dose CT scanning and gender or body mass index (BMI) of the patients, as well as the distribution of noise and artifact was evaluated. Results There was no statistical difference between the HU in sites of the phantom: lung (-777.3-- -758.2 HU, F=0.992, P<0.01), chest wall (107.9--111.3 HU, F=2.044, P>0.05), vertebra (835.6--875.3 HU, F=1.453, P>0.05), while the SD of which was of statistical signification: lung (9.5--29.0 HU, F=108.7, P<0.01), chest wall (10.1--32.4 HU, F=84.3, P<0.01), vertebra (19.2--57.1 HU, F=30.6, P<0.01),tbe SD increased with the decrease of the tube current. There was no statistical difference between male (in which 74 cases no or mild, 17 cases severe)and female (81 cases no or mild, and 28 cases severe)in image noise and artifact in low-dose images (X~2=2.294, P>0.05), and significant difference between groups of different BMI(in BMI<18.5 group, 29 cases no or mild,2 cases severe, in group of 18.5≤BMI<24.0, 120 cases no or mild, 13 cases severe, and in group of BMI≥24.0, 6 cases no or mild, 30 cases severe, X~2=128.274, P<0.01). The noise andartifact was greater in the upper (80 cases no or mild, 38 cases severe, X~2=18.918, P<0.01) and dorsal field (89 cases no or mild, 33 cases severe, X~2=6.760, P<0.05). Conclusions The image noise and artifact was significant in low-dose CT, especially in the dorsal and upper field of the lung, which might be attributed to the distribution of skeleton in the chest. It was recommended that scanning protocol (mAs value) be individualized adjusted in according to the patients BMI.

Objective To correlate dynamic parameters at contrast enhanced CT and interstitial fibrosis grade of non-small cell lung cancer (NSCLC). Methods Twenty-nine patients with NSCLC were evaluated by multi-slice CT. Images were obtained before and at 20,30,45,60,75,90,120,180,300,540,720,900 and 1200 s after the injection of contrast media, which was administered at a rate of 4 ml/s for a total of 420 mg I/kg body weight. Washout parameters were calculated. Lung cancer specimens were stained with hematoxylin-eosin stain and collagen and elastica double stain. Spearman test was made to analyze correlation between dynamic parameters and interstitial fibrosis grade of tumor. Results Twentynine NSCLC demonstrated washout at 20 min 12. 1 (0. 32-58.0 ) HU, washout ratio at 20 minutes 15.3% (0. 3%-39.2% ), slope of washout at 20 minutes 0. 0152 %/s ( 0. 0007%/s-0. 0561%/s ).Interstitial fibrosis of 29 lesions was graded as grade Ⅰ (10), grade Ⅱ (14) and grade Ⅲ (5). There were significant correlation between washout at 20 min ( r = - 0. 402, P ＜ 0. 05 ), washout ratio at 20 min ( r =-0.372,P＜0.05), slope of washout ratio (r = -0.459,P ＜0.05) and interstitial fibrosis grade in tumors. Conclusion NSCLC washout features at dynamic multi-detector CT correlates with interstitial fibrosis in the tumor.

Background Evaluation of acute myocardial infarction after reperfusion by dual phase contrast-enhancement multislice computed tomography (MSCT) was implicated in porcine model. There have been few attempts to use this diagnostic modality for the early assessment of coronary reperfusion in patients with ST-elevation myocardial infarction (STEMI), especially after primary percutaneous coronary intervention (PCI). In elderly patients with STEMI, the safety issues remain unknown. Methods Dual phase contrast-enhancement MSCT examinations were performed in 11 elderly patients (≥60 years old) with STEMI within one week after primary PCI. The presence, location and enhancement pattern on MSCT were evaluated. MSCT findings were compared with the catheter angiographic results and area under the curve of creatine kinase (CK) release. Serum creatinine level was recorded before and after MSCT scan. Results MSCT scans were successfully performed in all the patients. Early myocardial perfusion defect (early defect, ED) was detected in all of the 11 patients (100%) in the early phase of the contrast bolus (subendocardial ED in 10 patients and transmural in 1 patient). Mean CT attenuation value of ED was significantly different from CT attenuation value of remote myocardium (46±17 HU vs 104 ± 17 HU; P < 0.01). Location of ED area correlated well with infarction related artery territory on catheter angiography in all of the 11 patients (100%). On delayed phase of MSCT scan, different enhancement patterns were observed: isolated subendocardial late enhancement (LE) in 6 patients, subendocardial residual perfusion defect (RD) and subepicardial LE in 1 patient, subendocardial RD in 4 patients. Infarct volume assessed by MSCT correlated well with area under the curve CK release (R=0.72, P < 0.01). Serum creatinine level after MSCT scan showed no difference with that before MSCT scan. Conclusion Dual phase MSCT could be safely implicated in elderly patients with STEMI. Variable abnormal myocardial enhancement patterns were seen on dual phase MSCT in these patients with STEMI after primary PCI. Assessment of myocardial attenuation on MSCT gives additional information of the location and extent of infarction after reperfusion.

Objective To explore the changes of proteomic spectra from plasma of patients with lung cancer or benign lung diseases and health controls in order to establish a primary diagnosis model of lung cancer. Methods The proteomic spectra from plasma of 108 patients with lung cancer, 40 patients with benign lung diseases and 22 healthy individuals were analysed by surface-enhanced laser desorption/ionization time of flight mass spectrometry ( SELDI-TOF-MS). The best decision tree model was established by cluster analysis and principal component analysis. Then the model was blindly validated by the protein of 21 patients with lung benign diseases and 47 patients with stage I lung cancer. Results Twenty-three significantly differentially expressed protein peaks were successfully detected (P <0.001). Blinded validation suggested that the accuracy for diagnosing lung cancer was 72. 06%, the sensitivity and specificity were 72. 34% and 71.43%, respectively, and the positive predictive value and negative predictive value were 85. 0% and 78. 95%, respectively. Conclusion SELDI-TOF-MS protein chip technology provides a new tool for the early diagnosis of lung cancer.

Objective To evaluate the utility of multi-slice computed tomography (MSCT) in assessing acute non-reperfused myocardial infarct size. Methods Seven domestic pigs (mean weight 17.3 ± 1.9 kg) underwent ligation of the distal left anterior descending artery to establish a model of acute myocardial infarction (MI). MSCT and triphenyltetrazolium chloride (TTC) staining were performed two hours later. The following data were acquired and analyzed:MI volume (%), CT values of the infarcted region, left ventricular cavity and normal cardiac tissue at various scanning time-points (1, 5, 10, 15, 20 min after contrast injection). Results Using MSCT, the overall MI volume showed a time-dependent decrease, with a reduction of 28.87%after 20 min. The greatest reduction occurred at the 5 min time-point. In TTC staining, MI volume was 9.87%± 2.44%. When MI size, as determined by MSCT, was compared with that by TTC staining in Bland-Altman plots, there was a better agreement at 5, 10, and 15 min time-points at 1 and 20 min. Conclusions The study indicates that double-phase scanning examination using MSCT is a useful tool to assess MI size, and the optimal late-phase scanning time-point set within 5-15 min of contrast injection.

Objective: To evaluate the effectiveness of deep learning model trained on routine CT scans when identity the malignant and benign lung nodule on target CT scans dataset. Methods: This retrospective study enrolled 923 patients with lung nodules found by chest CT scan in Shanghai Chest Hospital from January 2016 to December 2018. A total of 969 nodules with pathological report were analyzed. The deep learning based pulmonary malignant prediction method in a fine-grained classification manner was used to make the prediction, and the AUC (the area under the curve), accuracy, sensitivity and specificity of routine CT scans and target CT scans were compared, and Delong test and IDI (Integrated Discrimination Improvement) were employed to provide statistical results. Furthermore, statistical methods were used to investigate the differences between the benign and malignant classification of nodules on routine CT and on target CT. Results: In the benign and malignant discrimination task, AUC, accuracy, sensitivity and specificity on the routine scans were 0.81, 82.0%, 86.0% and 56.6% respectively, while the AUC, accuracy, sensitivity and specificity on the target scans were 0.84, 85.0%, 88.8% and 60.5% respectively. The IDI was 0.056 (Z test, P<0.05), and there was statistically significant difference in ROC (Delong test, P=0.01). Conclusions The deep learning model trained on the data set of routine CT scans can achieve better diagnostic efficiency in target CT scans data.