不同病理类型的肺磨玻璃结节CT影像表现及相关性研究

目的 总结不同病理类型肺磨玻璃结节(GGN)的CT影像表现特点，探讨肺内GGN的CT影像表现与病理类型之间的相关性。方法 回顾性分析37例患者的43个肺GGN的临床、病理和CT影像资料，分析不同病理类型肺GGN的CT影像表现，探讨不同类型GGN的CT影像表现与病理类型之间的相关性。结果 37例患者手术切除共43个GGN,病理证实腺癌或腺体前驱病变(PGL)41个(腺癌24个，PGL17个),病理证实炎性病变2例。41个肿瘤性GGN的CT影像表现为：形态不规则8个、边缘分叶16个、结节内及邻近血管异常改变22个、胸膜凹陷征4个。肺GGN密度、形态、边缘及邻近结构在腺体前驱病变PGL组、微浸润腺癌MIA组、浸润性腺癌IAC组间的差异具有统计学意义(P<0.05);肺GGN直径和内部结构在各组间的差异无统计学意义(P>0.05)。结论 当肺GGN的CT影像出现形态不规则、边缘分叶、结节内及邻近血管异常改变、胸膜凹陷征等征象时，提示结节可能恶变，结合肺GGN患者的一般情况、临床资料、高危因素等综合考虑，可以提高肺GGN诊断的准确性。     

老年肺腺癌pGGN浸润前与浸润性病变的CT特征及病理对照

目的探讨纯磨玻璃密度结节(p GGN)浸润前与浸润性病变老年肺腺癌的CT特征及病理分离的对应关系。方法筛选190例(共194个病灶)经手术病理证实为肺腺癌且最大径≤1 cm的p GGN老年患者的CT图像和病理资料。按IASLC/ATS/ERS国际多学科分类解读标准进行病理分类:非典型腺瘤样增生(AAH)38个、原位腺癌(AIS)62个、微浸润腺癌(MIA)38个、浸润性腺癌(IPA)56个;浸润前病变(AAH+AIS)100个,浸润性病变(MIA+IPA)94个。比较不同病理亚型的CT征象,主要包括:病变部位、病灶大小、病灶密度、支气管气像、血管改变、病灶边缘、瘤肺界面。ROC曲线分析浸润前病变与浸润性病变的最佳临界值。结果 AAH病变大小明显小于AIS、MIA、IPA(P<0.05);AAH血管改变率低于AIS、MIA、IPA(P<0.05);AAH癌肺界面清晰率明显低于AIS、MIA、IPA(P<0.05);不同病理分型间病变部位分布、病灶密度、支气管气像发生率、病变边缘情况差异均无统计学意义(P>0.05)。ROC曲线分析显示,浸润前病变及浸润性病变大小的临界值为0.83 cm,敏感度为82.81%,特异度为81.50%,ROC曲线下面积为0.89。结论最大径≤1 cm的p GGN老年肺腺癌中病变大小、血管改变、瘤肺界面可用于浸润前与浸润性病变的鉴别诊断,其中病变大小0.83 cm可作为浸润前与浸润性病变的临界值。     

不同密度恶性孤立性肺结节临床及病理资料分析

目的总结并分析376例确诊为肺癌的不同密度孤立性肺结节患者的临床及病理资料。方法收集2015年1月1日至2017年12月31日于南京市胸科医院就诊并经术后病理确诊为肺癌的376例孤立性肺结节患者的临床及病理资料,根据结节密度分为纯磨玻璃结节组(p GGN组) 98例,混合磨玻璃结节组(m GGN组) 153例,实质性结节组(SN组) 125例并进行分析。结果 SN组患者年龄显著高于m GGN组及p GGN组(P 0. 01)。SN组出现咳痰、体重下降症状最多(P 0. 05)。SN组结节最大径显著高于p GGN组及m GGN组,p GGN组结节最小(P 0. 01)。SN组出现分叶征、毛刺征最多,其次为m GGN组及p GGN组(P 0. 01)。SN组原位腺癌最少,分化程度以中-低分化、低分化、差分化最多,出现送检淋巴结转移及脉管、胸膜、血管壁侵犯最多(P 0. 01)。结论 CT表现不同密度的孤立性结节肺癌、临床症状、影像表现及术后病理不同,恶性实质性结节较混合磨玻璃结节及纯磨玻璃结节,恶性程度最高。     

不同病理类型肺部磨玻璃结节的CT影像学及EGFR基因突变特征

目的 探究不同病理类型肺部磨玻璃结节（GGN）的CT影像学及表皮生长因子受体（EGFR）基因突变特征。方法 选取肺部GGN患者80例,其中非典型腺瘤样增生10例、原位癌15例、微浸润腺癌（MIA）35例、浸润性腺癌（IA）。采用多层螺旋CT(MSCT)观察肺部GGN的CT值、病灶大小、二维比率、三维比率以及肺部征象、瘤周边缘、边界清晰度、病灶形状等影像学特点。应用二代测序技术检测GGN样本EGFR基因第18、19、20及21外显子的突变状态。结果 随着恶性程度增加,GGN的CT值、病灶增大,不同病理类型GGN的CT值、病灶大小比较差异有统计学意义（P均<0.05）。不同病理类型GGN肺部征象、结节边界以及病灶形状比较差异有统计学意义（P均<0.05）。80例患者发生EGFR基因突变35例,EGFR总突变率为43.75%,主要为外显子19(Ex19Del)和外显子21(L858R)突变。MIA与IA患者EGFR基因突变率比较差异有统计学意义（P<0.05）。结论 不同病理类型GGN患者MSCT影像学特征不同,随着恶性程度增加,GGN的CT值、病灶增大,发生胸膜凹陷征、血...     

老年人周围型肺结节良恶性CT征象及处理

目的总结老年周围型肺结节的良恶性CT征象。方法所有病例术前均行高分辨率CT(HRCT)检查,统计学分析结节大小、形态、边缘及磨玻璃成分、内部特征在各病理组间差异。结果磨玻璃结节大小及磨玻璃成分在各病理组间差异显著,形态、边缘及内部特征无统计学差异;实性结节大小、边缘特征在各病理组间有统计学差异,形态特征无统计学差异。结论 HRCT在≤10 mm的周围型肺结节的良恶性鉴别上有一定价值,较大结节(8~10 mm)及实性成分的存在(m GGN)或具有分叶特征的实性结节高度提示恶性肿瘤可能。     

磨玻璃结节预测非小细胞肺癌浸润的研究

目的 研究磨玻璃结节（GGN）预测非小细胞肺癌（NSCLC）浸润的情况。方法 回顾性选择2014年1月至2019年6月经手术切除病理证实为GGN型NSCLC患者244例,分析其CT特征和病理检查结果,评估GGN与NSCLC浸润的关联性。结果 244例GGN病理检查为腺癌,其中原位腺癌（AIS）44例,微浸润腺癌（MIA）53例,浸润性腺癌（IA）147例。9例支气管充气征GGN病理结果全部为IA。2例存在淋巴结转移。AIS组、MIA组和IA组在密度、分叶、毛刺、空泡征、支气管充气征、胸膜牵拉征、血管集束征,以及实性成分大小、实性成分比例和结节最大径方面比较差异有统计学意义（P<0.05）。受试者工作特征（ROC）曲线分析结果显示,结节最大径、实性成分大小、实性成分比例具有预测NSCLC是否浸润的价值,其中以结节最大径的诊断效能最佳。结论 GGN大小可用于预测NSCLC是否浸润。     

人工智能影像系统预测肺结节良恶性及浸润性的临床初探

目的 评估人工智能辅助诊断系统对肺结节定性诊断的准确性及预测肺腺癌浸润程度的临床应用价值。方法 回顾性分析本院2021年1月至2022年1月经手术病理证实的肺结节患者。将肺结节分为恶性肿瘤组和良性病变组，其中肺腺癌又分为浸润性腺癌组和非浸润性腺癌组。将各组肺结节影像资料导入人工智能辅助诊断系统，记录量化参数、恶性概率及预测病理亚型，并采用受试者工作特征曲线评估人工智能诊断系统鉴别良恶性肺结节的效能及预测肺腺癌侵袭程度的临床价值。结果 人工智能诊断与病理结果的一致性检验的Kappa值为0.676(P<0.001)。人工智能组鉴别良恶性肺结节的ROC曲线下面积为0.91,敏感度94.3%,特异度70.2%;医师阅片组的ROC曲线下面积为0.767,敏感度80.5%,特异度63.3%。两组患者临床资料比较，年龄、性别、恶性概率、CT平均值和CT最大值差异有统计学意义(P<0.05)。人工智能自动预测肺腺癌侵袭程度的ROC曲线下面积为0.808,敏感度71.0%,特异度89.7%。结论 人工智能系统对肺结节定性诊断与肺结节病理结果的一致性好，对早期肺癌诊断具有重要意义，并且能自动预...     

肺结节分析技术对肺内局灶性磨玻璃结节的CT诊断价值

目的通过病理对照探讨肺结节分析技术对肺内局灶性磨玻璃结节的CT诊断价值。方法分析61例肺内磨玻璃结节的CT影像资料,良性病变5例,浸润前病变15例(其中非典型腺瘤样增生(AAH)6例,原位腺癌(AIS)9例),浸润性病变42例,(其中微浸润癌(MIA)1例,浸润性腺癌(IAC)41例)。结果 61例肺磨玻璃结节中纯磨玻璃结节p GGN20例,混合磨玻璃结节m GGN41例。p GGN中,良性病变4例,浸润前病变15例,1例为浸润性腺癌;m GGN多为浸润性腺癌,本组病例40例为浸润性腺癌;良性病变、浸润前病变多为纯磨玻璃结节,形态规整,多为圆形或类圆形,边界清晰;浸润性病变多为混合磨玻璃结节,形态多不规则,边界清晰,边缘毛刺及分叶多见,内部空泡、胸膜凹陷,血管集束征较良性病变、浸润前病变多见。病灶与支气管的关系,浸润性腺癌组以Ⅰ-Ⅲ型多见,良性病变及浸润前病变以Ⅳ-Ⅴ型常见。结论了解肺结节分析技术,熟悉磨玻璃结节的CT影像特征,对诊断和鉴别诊断肺部良性病变、浸润前病变、IAC具有重要价值。     

肺磨玻璃结节CT值测量在早期癌症诊断中的意义

<正>随着多层螺旋CT的广泛应用及低剂量CT扫描在早期肺癌筛查中的开展,肺小结节的检出率明显提高,特别是肺内磨玻璃结节(ground-glass nodules,GGN)即肺部早期癌症的检出和早期手术治疗的开展,患者术后生存率明显提高。GGN是一种有特征性而非特异性的近年提出的CT影像表现。任何只要肺实质含气量减少、细胞密度增加,此时肺泡尚未完全萎陷,CT图像上即可出现磨玻璃样阴影。它可以是良性病变,如炎症或出血,也可以是肺腺癌浸润的癌前病变,如腺瘤样增生、原位腺癌等[1]。GGN多位于肺组织外周,以腺癌为主。磨玻璃结节因其就诊时发现的时间不同,所以其密度也有差异,CT值测量最低的可以是-700 Hu,仅     

高分辨CT表现对孤立性肺结节良恶性鉴别的研究进展

<正>孤立性肺结节(SPN)无肺不张、肺门增大或胸腔积液的表现〔1〕;SPN在胸部X线片中的检出率只有0.09%~0.20%,多数是在不经意间发现〔2〕,随着高分辨率CT(HRCT)的广泛应用,越来越多地被发现并得到重视。同时根据直径,SPN分为直径≤8 mm的亚厘米结节、8 mm结节≤3 cm的典型SPN,再根据CT上是否存在磨玻璃样变结节(GGN),将SPN分为纯磨     

Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model

BackgroundPatients with consistent lung pure ground-glass nodules (pGGNs) have a high incidence of lung adenocarcinoma that can be classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Regular follow-up is recommended for AIS and MIA, while surgical resection should be considered for IAC. This study sought to develop a multi-parameter prediction model to increase the diagnostic accuracy in discriminating between IAC and AIS or MIA.MethodsThe training data set comprised consecutive patients with lung pGGNs who underwent resection from January to December 2017 at the Zhongshan Hospital. Of the 370 resected pGGNs, 344 were pathologically confirmed to be AIS, MIA, or IAC and were included in the study. The 26 benign pGGNs were excluded. We compared differences in the clinical features (e.g., age and gender), the content of serum tumor biomarkers, the computed tomography (CT) parameters (e.g., nodule size and the maximal CT value), and the morphologic characteristics of nodules (e.g., lobulation, spiculation, pleura indentation, vacuole sign, and normal vessel penetration or abnormal vessel) between the pathological subtypes of AIS, MIA, and IAC. An abnormal vessel was defined as “vessel curve” or “vessel enlargement”. Statistical analyses were performed using the chi-square test, analysis of variance (ANOVA), and rank test. The IAC prediction model was constructed via a multivariate logistical regression. Our prediction model for lung pGGNs was further validated in a data set comprising consecutive patients from multiple medical centers in China from July to December 2018. In total, 345 resected pGGNs were pathologically diagnosed as lung adenocarcinoma in the validation data set.ResultsIn the training data set, patients with pGGNs ≥10 mm in size had a high incidence (74.5%) of IAC. The maximal CT value of IAC [–416.1±121.2 Hounsfield unit (HU)] was much higher than that of MIA (–507.7±138.0 HU) and AIS (–602.6±93.3 HU) (P<0.001). IAC was more common in pGGNs that displayed any of the following CT manifestations: lobulation, spiculation, pleura indentation, vacuole sign, and vessel abnormality. The IAC prediction model was constructed using the parameters that were assessed as risk factors (i.e., the nodule size, maximal CT value, and CT signs). The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this model for diagnosing IAC was 0.910, which was higher than that of the AUC for nodule size alone (0.891) or the AUC for the maximal CT value alone (0.807) (P<0.05, respectively). A multicenter validation data set was used to validate the performance of our prediction model in diagnosing IAC, and our model was found to have an AUC of 0.883, which was higher than that of the AUC of 0.827 for the module size alone model or the AUC of 0.791 for the maximal CT value alone model (P<0.05, respectively).ConclusionsOur multi-parameter prediction model was more accurate at diagnosing IAC than models that used only nodule size or the maximal CT value alone. Thus, it is an efficient tool for identifying the IAC of malignant pGGNs and deciding if surgery is needed.     

Incremental value of contrast enhanced computed tomography on diagnostic accuracy in evaluation of small pulmonary ground glass nodules

Background

To evaluate the information gain by the application of both non-contrast and contrast enhanced computed tomography (CT) with extended mediastinal display window settings in the evaluation of pure ground glass nodules (pGGNs) and or mixed ground glass nodules (mGGNs) in the context of pre-invasive or early stage lung adenocarcinoma.

Methods

One hundred and fifty patients with ground glass nodules (GGNs) and mGGNs, with contrast enhanced CT scans within 2 weeks of thoracic surgery were included in the study. Quantitative evaluation of all nodules was performed in a conventional mediastinal window (CMW) and an extended mediastinal window (EMW) both on non-contrast images and contrast-enhanced images.

Results

Contrast-enhanced images with CMW demonstrated amplification of solid portion in 23 (43%), 41 (77%) with EMW out of 53 minimally invasive adenocarcinoma (MIA) nodules, and in 34 of 37 (91%) of invasive adenocarcinoma (IAC) nodules. Using the increase in size of solid portion of the nodule measured on the enhanced CT images with EMW, area under the receiver operating characteristic (ROC) curve of 0.872 and 0.899 was utilized for differentiating between the pre-invasive nodules and MIA and between MIA and IAC nodules, respectively. Statistically significant differences existed between the pre-invasive and the MIA groups, and MIA and the IAC groups in smaller nodules (P<0.01).

Conclusions

Comparative quantitative analysis of the pre and post contrast images can help differentiate between atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), MIAs, and IACs. Extension of the CT mediastinal window setting improves the evaluation of small GGNs, and can augment the diagnostic accuracy when evaluating small pGGNs and mGGNs.     

Can peritumoral regions increase the efficiency of machine-learning prediction of pathological invasiveness in lung adenocarcinoma manifesting as ground-glass nodules?

BackgroundThe peri-tumor microenvironment plays an important role in the occurrence, growth and metastasis of cancer. The aim of this study is to explore the value and application of a CT image-based deep learning model of tumors and peri-tumors in predicting the invasiveness of ground-glass nodules (GGNs).MethodsPreoperative thin-section chest CT images were reviewed retrospectively in 622 patients with a total of 687 pulmonary GGNs. GGNs are classified according to clinical management strategies as invasive lesions (IAC) and non-invasive lesions (AAH, AIS and MIA). The two volumes of interest (VOIs) identified on CT were the gross tumor volume (GTV) and the gross volume of tumor incorporating peritumoral region (GPTV). Three dimensional (3D) DenseNet was used to model and predict GGN invasiveness, and five-fold cross validation was performed. We used GTV and GPTV as inputs for the comparison model. Prediction performance was evaluated by sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).ResultsThe GTV-based model was able to successfully predict GGN invasiveness, with an AUC of 0.921 (95% CI, 0.896–0.937). Using GPTV, the AUC of the model increased to 0.955 (95% CI, 0.939–0.971).ConclusionsThe deep learning method performed well in predicting GGN invasiveness. The predictive ability of the GPTV-based model was more effective than that of the GTV-based model.     

Correlation of computed tomography quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma

The purpose of the study is to investigate the correlation of computed tomography (CT) quantitative parameters with tumor invasion and Ki-67 expression in early lung adenocarcinoma.The study involved 141 lesions in 141 patients with early lung adenocarcinoma. According to the degree of tumor invasion, the lesions were assigned into (adenocarcinoma in situ + minimally invasive adenocarcinoma) group and invasive adenocarcinoma (IAC) group. Artificial intelligence-assisted diagnostic software was used to automatically outline the lesions and extract corresponding quantitative parameters on CT images. Statistical analysis was performed to explore the correlation of these parameters with tumor invasion and Ki-67 expression.The results of logistic regression analysis showed that the short diameter of the lesion and the average CT value were independent predictors of IAC. Receiver operating characteristic curve analysis identified the average CT value as an independent predictor of IAC with the best performance, with the area under the receiver operating characteristic curve of 0.893 (P < .001), and the threshold of –450 HU. Besides, the predicted probability of logistic regression analysis model was detected to have the area under the curve of 0.931 (P < .001). The results of Spearman correlation analysis showed that the expression level of Ki-67 had the highest correlation with the average CT value of the lesion (r = 0.403, P < .001).The short diameter of the lesion and the average CT value are independent predictors of IAC, and the average CT value is significantly positively correlated with the expression of tumor Ki-67.     

上海肺科医院110例肺部磨玻璃样结节临床诊治分析

目的观察肺部磨玻璃样结节(ground-glass nodule,GGN)的影像学特点、病理类型和手术效果。方法收集上海肺科医院因为GGN住院手术的完整病历110例。观察病人的性别、年龄、入院方式、平均住院时间、胸部X线片及胸部CT影像学特点、肿瘤标志物检查情况、气管镜检查情况、手术方式、病理类型分布、手术并发症等。结果 GGN(ground-glass nodule磨玻璃样结节)患者多无呼吸道症状和体征,肿瘤标志物检查阳性率低,气管镜检查阳性低,胸片检查漏诊率高,胸部CT可有效发现肺部隐蔽病灶,病理检查恶性率高,以腺癌为主,电视辅助胸腔镜手术创伤小,手术并发症少。结论胸部CT可作为常规体检项目,肺部高度疑癌磨玻璃样结节要尽早行电视辅助胸腔镜手术,以提高早期肺癌的治愈率。     

超高分辨率CT靶扫描与CT靶重建在肺磨玻璃样结节定性诊断中的价值

目的 比较超高分辨率CT(UHRCT)靶扫描与常规CT靶重建的肺磨玻璃样结节微征象,分析这两种方法对肺磨玻璃样结节定性诊断的价值。方法 收集2016年8月至2017年12月在山东省胸科医院筛查疑诊为肺结核的患者120例。本组患者CT扫描均发现有肺内单发磨玻璃样结节影。患者行常规CT扫描,然后进行靶重建和UHRCT靶扫描,共计结节灶120个。由2名副高级以上诊断医师阅片,分析上述两种CT成像技术所显示的肺磨玻璃样结节征象(结节边缘、增粗肺纹理、结节内实性成分、毛刺征、空泡征、支气管征、胸膜牵拉征),分别定性诊断癌前病变[不典型腺瘤样增生(AAH)、肺原位腺癌(AIS)]、微浸润腺癌(MIA)、浸润腺癌(IAC),最终根据病理结果比较两种成像技术对肺腺癌分期诊断的正确率。采用SPSS 17.0软件进行统计学处理,计数资料用卡方检验,以P<0.05差异具有统计学意义。结果 结节边缘清晰,UHRCT靶扫描为71个(78.0%),CT靶重建为56个(61.5%)(χ ²=5.863,P=0.015)。肺纹理增粗,UHRCT靶扫描为60个(65.9%),CT靶重建为45个(49.5%)(χ ²=5.065,P=0.024)。结节内实性成分,UHRCT靶扫描为66个(72.5%),CT靶重建为50个(54.9%)(χ ²=6.086,P=0.014)。毛刺征UHRCT靶扫描为34个(37.4%),CT靶重建为29个(31.9%)(χ ²=0.319,P=0.572)。空泡征UHRCT靶扫描为22个(24.2%),CT靶重建为18个(19.8%)(χ ²=0.513,P=0.474)。支气管征UHRCT靶扫描为28个(30.8%),CT靶重建为26个(28.6%)(χ ²=0.105,P=0.746)。胸膜牵拉征UHRCT靶扫描为30个(33.0%),CT靶重建为21个(23.1%)(χ ²=2.207,P=0.137)。常规CT靶重建诊断与病理符合数为75个(82.4%),不符合数为16个(17.6%)。UHRCT靶扫描检查与病理符合数为86个(94.5%),不符合数为5个(5.5%)(χ ²=6.513, P=0.011)。 结论 UHRCT靶扫描较常规CT靶重建显示的肺磨玻璃样结节微征象更清楚,有助于对肺磨玻璃样结节的病理分期。     

多层螺旋CT薄层靶成像技术鉴别诊断肺部磨玻璃结节的价值

目的 探讨多层螺旋CT薄层靶成像技术诊断肺部磨玻璃结节（GGN）的价值。方法回顾性分析2018年1月至2021年7月于怀来县中医医院行64排螺旋CT检查发现并经病理证实的GGN患者76例。其中良性GGN32例,恶性GGN44例。所有患者均行5 mm层厚常规螺旋CT扫描和1 mm薄层螺旋CT靶成像重建。比较良、恶性GGN影像学特征及形态特征,以及64排螺旋CT不同层厚显示效果。结果 良、恶性GGN的分叶征、空泡征、胸膜凹陷征、毛刺征及边缘欠清晰等差异均有统计学意义（P<0.05）;良、恶性GGN的形态不规则、形态规则呈圆或椭圆形、斑片状及多结节融合等差异均有统计学意义（P<0.05）。5 mm层厚常规螺旋CT扫描与1 mm薄层螺旋CT靶成像重建对GGN分叶征、空泡征、胸膜凹陷征、边缘欠清晰、毛刺征的检出率差异均有统计学意义（P<0.05）。1 mm薄层靶成像技术呈现的影像学特征明显优于5 mm层厚常规CT扫描。结论 64排螺旋CT薄层靶成像技术的应用对良、恶性GGN的鉴别诊断具有较高的临床应用价值,能明显提高早期肺癌的检出率,为临床诊疗提供参考。     

Prognosis and status of lymph node involvement in patients with adenocarcinoma in situ and minimally invasive adenocarcinoma—a systematic literature review and pooled-data analysis

Background

Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) have been brought up that substitute for bronchioloalveolar carcinoma (BAC), according to the new classification of lung adenocarcinoma. There has been increasing opinions that argues for the adjustment of lymph node disposition in patients with such early stage tumors. Therefore, we sought to overview the prognosis and status of lymph node involvement in AIS/MIA patients.

Methods

PubMed, Springer and Ovid databases were searched for relevant studies. Data was extracted and results summarized to demonstrate the disposition of lymph nodes in AIS/MIA.

Results

Twenty-three studies consisting of 6,137 lung adenocarcinoma were included. AIS/MIA accounted for 821 of the total 6,137. All included patients received curative surgery. After a review of the summarized data we found that only one patient (with MIA) had N1 node metastasis, N2 disease was not found in any of the included patients. In concordance with this, studies that reported 5-year disease free survival (5-year DFS) have almost 100% rate.

Conclusions

Our findings indicated that patients with AIS/MIA have good survival prognosis after surgical resection, and that recurrence and lymph node metastasis in these patients is rare. Therefore, we strongly encouraged further studies to determine the role of different lymph node disposition strategies.     

直径<1cm肺腺癌浸润进展影响因素及临床预后探讨

目的:探讨直径<1cm肺浸润性腺癌发生独立影响因素及临床预后。方法回顾性分析我院2013年1月-2018年3月收治直径<1cm肺腺癌患者共364例临床资料,根据胸部影像学特征分组,其中pGGN(A组)122例,mGGN(B组)136例,SN(C组)106例,比较三组基线临床特征和手术相关指标,分析结节直径亚组病理相关指标和分期差异,采用Logistic回归模型评价直径<1cm肺浸润性腺癌发生独立影响因素。结果①364例患者均胸腔镜手术治疗,其中楔形切除,切缘距病灶均<2cm。C组肺叶切除比例显著高于A组、B组(P<0.05);男性吸烟比例显著高于女性(P<0.05);②122例pGGN患者中1~5mm病灶术后病理均为原位/微浸润腺癌;A组6~10mm病灶Ia1期比例显著高于1~5mm病灶(P<0.05)。mGGN中6~10mm病灶共92例,包括胸膜侵犯6例,脉管癌栓2例;SN中6~10mm病灶共78例,包括胸膜侵犯10例,脉管癌栓4例,淋巴结转移4例。③单因素分析结果显示,AIS+MIA和IAC组吸烟史、既往癌症罹患史、病灶影像学特征及病灶直径比较,差异有统计学意义(P<0.05);多因素分析结果显示,吸烟史、既往癌症罹患史、mGGN、SN及病灶直径>5mm,均是直径<1cm肺浸润性腺癌独立危险因素(P<0.05)。④364例患者中肺叶切除术后住院期间因肺栓塞死亡1例,随访时间为20~81个月,中位随访时间为43.0个月;随访过程中Ia1期患者中1例在术后14个月因肺炎死亡;随访总生存率为99.72%(362/363)。结论直径<1cm肺浸润性腺癌患者中mGGN和SN如病灶直径达6~10mm,更易累及胸膜或淋巴结;吸烟史、既往癌症罹患史、mGGN、SN及病灶直径>5mm均与直径<1cm肺浸润性腺癌发生独立相关。     

Focal ground-glass opacity detected by low-dose helical CT

OBJECTIVE: Focal ground-glass opacity (GGO) has been detected increasingly by low-dose helical CT. Although focal GGO suggests in situ neoplastic lesion in the peripheral lung, it remains controversial how to manage these lesions. The purpose of this study was to evaluate the pathologic and radiologic characteristics of focal GGO in order to develop a standard of treatment for these lesions. PATIENTS: Forty-three patients with persistent focal GGO < or = 2 cm in size from January 1998 to September 2000 were studied. Thoracoscopic lung biopsy was performed consecutively for persistent focal GGO following a several-month observation period (mean, 3.7 months). RESULTS: The histologic diagnoses were bronchioloalveolar carcinoma (BAC) in 23 patients, adenocarcinoma with mixed subtypes in 11 patients, and atypical adenomatous hyperplasia (AAH) in 9 patients. None of 34 carcinoma patients had lymph node involvement. All of 17 lesions > or = 1 cm in size were malignant. GGO with solid components on high-resolution CT were highly associated with adenocarcinoma (malignant rate, 93.3%). CONCLUSIONS: Persistent focal GGO after observation for several months was a finding of early adenocarcinoma or its precursor. Especially, lesions > or = 1 cm in size or GGO with solid component were significant signs of malignancy. We concluded lung biopsy should be attempted for persistent focal GGO.