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作 者:邹勤[1] 范丽[1] 李琼[1] 李清楚[1] 管宇[1] 夏艺[1] 望云[1] 顾亚峰 刘士远[1] 萧毅[1]
机构地区:[1]第二军医大学长征医院影像科,上海200003
出 处:《实用放射学杂志》2016年第11期1681-1684,1695,共5页Journal of Practical Radiology
基 金:国家自然基金项目(81370035,81230030);上海科学技术委员会生物医药重大专项项目(13411950100).
摘 要:目的研究肺磨玻璃密度结节(GGN)MDCT定量分析与不同病理类型的相关性。方法回顾性分析病理证实的181例肺GGN,根据病理结果分成浸润前病变[包括非典型腺瘤样增生(AAH)和原位腺癌(AIS)]、微浸润腺癌(MIA)和浸润性腺癌(IPA)3组。将原始CT图像0.625mm或1mm薄层重建后,手动勾画出肿瘤的边界,经in-houseprogram自动分析肿瘤的横断面最大径、垂直于最大径的垂直径,平均密度和体积。再计算出肿瘤的平均大小[(最大径+垂直径)/2]、质量[(平均密度+1000)×体积/100]。进行逐步判别分析,建立判别方程。结果经非参数Kruskal-WallisH检验得出,4个CT定量参数在3组之间存在统计学差异(P〈0.001)。经Mann-Whitney U检验,浸润前病变、MIA的4个MDCT定量参数均明显低于IPA组(P〈0.001);而浸润前病变与MIA的4个MDCT定量参数之间均无统计学差异(P〉O.05)。经逐步判别分析得出,平均大小、平均密度和质量在3组病变的判别中具有重要价值,用这3个指标联合进行判别的准确率是71.3%,交叉判别的准确率是69.6%。结论GGN的平均大小越大,平均密度越高,体积、质量越大,其为IPA的概率越大。平均大小、平均密度和质量是区分病灶有无浸润性的重要参数。Objective To evaluate the correlation between CT quantitative parameters and different subtype of peripheral pulmo- nary adenocarcinoma manifesting as ground-glass nodule (GGN). Methods 181 GGNs confirmed by pathology were analyzed retro- spectively. All pathologic specimen were classified into preinvasive lesions [atypical adenocarcinoma hyperplasia (AAH) or adeno- carcinoma in situ (AIS) ], minimally invasive adenocarcinoma (MIA) and invasive pulmonary adenocarcinoma (IPA). All raw data- sets were reconstructed into 0. 625 mm or 1 mm of thickness, and then the border of the nodule was manually depicted slice by slice. The maximum cross-sectlonal diameter, vertical diameter perpendicular to the maximum diameter, mean density and volume were automatically calculated by an in-house software program. Then, the mean size and mass of the nodule were calculated. Stepwise discriminant analysis was used to establish the discriminant model. Results The Kruskal-Wallis H test prove that four MI)CT quantitative parameters, including mean size, volume, mass, and mean density were significantly different (P〈0. 001) among the three groups. The Mann-Whitney U test prove that four parameters were significantly different (P〈0. 001 ) between preinvasive lesions and IPA, or between MIA and IPA. No differences were found in all the four parameters between preinvasive lesion and MIA. Mean size, mean density and mass were selected according to stepwise discriminant analysis. The accuracy of Bayes mode was 71.3% and 69.6% by using substitution method and cross validation method respectively. Conclusion The GGN with larger mean size and volume, greater density and mass, has a higher probability of IPA than that of MIA or preinvasive lesion. Mean size, mean density and mass are the important parameters to differentiate the different subtypes of pulmonary adenocarcinomas.
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