RESUMO
Objective:To evaluate the value of a novel multiphase three-dimensional deep learning neural network of computer-aided diagnosis (CAD) used in LDCT lung cancer screening.Methods:Eight thousand eight hundred and fifty volunteers with 1 111 nodules were enrolled in the lung cancer screening from November of 2013 to December of 2017, and the baseline LDCT imaging data of volunteers accompanied with clinical information were retrospectively analyzed. All volunteers in this study were designed to receive LDCT test at least once. All the imaging of volunteers were read through the methods of visual detectioin (VD), CAD, and VD Combined CAD. The criteria of the true pulmonary nodule was determinated by the consistent opinion of two specialists in chest imaging（in case of disagreement, the decision should made by the third chief physician). In terms of the numbers, types or Lung-RADS categories of nodules, the detection rate, missed diagnosis rate and false positive rate of pulmonary nodules or lung cancer among three methods were compared, and the rates between groups were compared by χ 2test. Results:Compared with VD or CAD ,the detection rate of nodules in the CAD combined VD was significantly increased (95.7% , 94.2%, vs. 80.1% P<0.05 ), and the rate of missed diagnosis was significantly reduced (5.8%, 4.3% vs. 19.9% ，χ2=101.650, 128.500 ，P<0.05); Compared with VD, the methods of CAD or VD combined CAD significantly increased the the detection rates of Lung-RADS categories (χ2 =25.083,23.449, P=0.000, 0.000) or different types of nodules (χ2=6.955,6.821, P=0.031, 0.033), but there was no statistically significant difference between CAD and VD combined CAD for Lung-RADS categories and different types of nodules (all P>0.05); Compared with VD and VD combined CAD, the positive prediction rate of CAD for lung cancer was significantly reduced, and the rate of missed diagnosis and false positive rate were significantly increased, but there was no significant difference between VD and VD combined CAD in the prediction rate, missed diagnosis rate and false positive rate of lung cancer. Conclusion:The method of CAD combined VD can reduce the detection of false positive nodules and improve the detection rate of true pulmonary nodules,which is the preferred method using in LDCT lung cancer screening for city population.
RESUMO
Objective To investigate the correlation between quantitative parameters of dynamic contrast?enhanced MRI (DCE?MRI) after neoadjuvant chemotherapy and pathological grades in esophageal squamous cell carcinoma. Methods Fifty?six patients with esophageal squamous cell carcinoma who were confirmed by esophagoscope and received neoadjuvant chemotherapy before operation between September 2015 and December 2017 in the Affiliated Cancer Hospital of Zhengzhou University were prospectively analyzed, and MRI examination was performed within one week before operation. All patients underwent routine chest MRI and DCE?MRI scanning, and quantitative parameters of DCE?MRI, including volume transfer constant (Ktrans),exchange rate constant (Kep) and extravascular extracellular volume fraction (Ve) were measured. Pathological grading was assessed as highly differentiated, moderately differentiated, poorly differentiated,and undifferentiated. Intraclass correlation coefficient (ICC) was calculated from the results of two radiologists. Kruskal?Wallis H test was used to compare the differences of quantitative parameters between different pathological grade groups of DCE?MRI,and Mann?Whitney U test was utilized to compare the intraclass differences among pathological grades. Spearman rank correlation analysis was performed for evaluating the correlation between DCE?MRI parameters and pathological grade of esophageal squamous cell carcinoma. The receiver operating characteristic (ROC) curves were used to evaluate the diagnosis accuracy of different DCE?MRI parameters in pathological grade of esophageal squamous cell carcinoma after neoadjuvant chemotherapy. Results The 56 patients were divided into four groups according to pathological findings: well differentiated group (n=8), moderately differentiated group (n=39), poorly differentiated group (n=9) and undifferentiated group (n=0). The differences of Ktransmean,Ktrans75%,Kepmax, Kepmean,Kep75% between different pathological grading groups were statistically significant (all P<0.05),and these parameters showed positive correlation significantly with pathological grading (r values were 0.778, 0.632, 0.594, 0.725, 0.489 respectively, all P<0.05). The ROC curve area of Ktransmean, Ktrans75% in the diagnosis of pathological grade for esophageal squamous cell carcinoma was 0.750,0.856,respectively. The diagnostic efficiency of Ktrans75% was the best with the diagnostic threshold of 0.693/min,sensitivity of 87.5%, specificity of 78.5%, respectively. Conclusion The quantitative parameters of DCE?MRI after neoadjuvant chemotherapy in esophageal squamous cell carcinoma have the potential value for predicting pathological grade.