基于Myrian影像后处理系统的CT诊断技术在早期肺癌筛查与诊断中的应用价值

刘利; 毛小博; 蒋浩; 马永峰

doi:10.3969/j.issn.2095-5227.2021.01.008

基于Myrian影像后处理系统的CT诊断技术在早期肺癌筛查与诊断中的应用价值

Application value of CT diagnosis technology based on Myrian image post-processing system in screening and diagnosis of early lung cancer

摘要

摘要:
背景肺癌的发病率逐年升高，早期诊断、早期治疗，提高其5年存活率，同时避免一些良性肺部结节接受不必要的外科手术对于肺癌患者管理非常重要。
目的探讨基于Myrian影像后处理系统的CT诊断技术在早期肺癌筛查与诊断中的应用价值。
方法选择2016年11月- 2019年5月沧州市人民医院胸外科收治的70例未明确性质且高度怀疑为早期肺癌的肺结节患者作为研究对象。所有患者均接受胸部螺旋CT检查，并经手术切除证实结节性质，将原始CT薄层轴位影像数据传输至工作站并应用Myrian后处理软件进行病灶及周围肺组织、气管的三维重建，根据最终影像结果进行诊断并确定肺结节恶性风险的相关指标。
结果 70例疑似早期肺癌的肺结节患者共94处结节灶，CT扫描显示所有肺结节直径均小于3 cm。经病理学证实为早期肺癌56处，良性结节38处。Myrian后处理技术判断为恶性可能57处，良性可能37处。与金标准比较，Myrian后处理技术诊断早期肺癌的准确率为88.30%，敏感度为91.09%，特异性为84.21%。单因素logistic回归分析显示Myrian重建后获取的三维形状、病灶位置、结节容积、边缘形态对恶性结节具有预测价值(P＜0.05)，多因素logistic回归分析显示结节容积 ≥ 500 mm³、三维边缘形态为分叶/毛刺/不规则状具有预测恶性结节的价值(HR均＜1，P均＜0.05)。
结论 Myrian后处理技术可将普通CT断层影像重建为三维图像，清晰显示肿瘤与周围气管、支气管、血管的空间关系，对早期肺癌具有一定的诊断价值。

Abstract:
Background The incidence of lung cancer is increasing year by year, and it is of great importance for lung cancer patients to receive early diagnosis and treatment, to improve the 5-year survival rate, and avoid some benign pulmonary nodules from receiving unnecessary surgical intervention.
Objective To evaluate the CT diagnosis technology based on Myrian image post-processing system in early lung cancer screening and diagnosis.
Methods From November 2016 to May 2019, 70 patients with pulmonary nodules who were suspected to be early lung cancer were selected as the study subjects. All patients received chest spiral CT examination, and confirmed the nature of the nodules by pathology results after surgical resection. The original CT thin-layer axial image data were sent to the workstation, and the three-dimensional reconstruction of the lesions, surrounding lung tissue and trachea was performed by Myrian post-processing software.
Results There were 94 nodules in 70 patients, which were confirmed by pathology as 56 malignant and 38 benign nodules. CT scan showed that all the nodules were less than 3 cm in diameter. Myrian postprocessing diagnosed 57 nodules as malignant and 37 as benign. Compared with the gold standard, the accuracy of Myrian postprocessing in diagnosing early lung cancer was 88.30%, with the sensitivity and specificity of 91.09% and 84.21% respectively. Univariate logistic regression analysis showed that shape, lesion location, nodule volume and border shape obtained after Myrian reconstruction were of predictive value for malignant nodules (P＜0.05). Multiple logistic regression analysis showed that the size of nodules ≥ 500 mm³, and irregular, lobulated or burr-like boundaries, had the value of predicting malignant nodules (HR＜1, P＜0.05).
Conclusion Common CT images can be reconstructed into three-dimensional images by Myrian post-processing technology, which can clearly show the spatial relationship between tumor and surrounding trachea, aiding the diagnosis of early lung cancer with high accuracy.

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