Clinical characteristics of 323 patients with postoperative pathological diagnosis of benign pulmonary nodules

doi:10.3877/cma.j.issn.2095-8773.2024.03.04

Abstract

Abstract:

Objective

To analyze the clinical characteristics of patients with postoperative pathological diagnoses of benign pulmonary nodules, providing diagnostic insights to distinguish benign nodules and reduce unnecessary surgical interventions.

Methods

A retrospective analysis was conducted on the clinical data of 323 patients diagnosed with benign pulmonary nodules postoperatively at the First Affiliated Hospital of the University of Science and Technology of China from January 2021 to June 2023. Statistical analysis was used to evaluate the clinical features, imaging characteristics, and postoperative pathological results of these patients. Based on the postoperative pathological results, the patients were divided into a non-surgical indication benign nodule group (113 cases) and a surgical indication benign nodule group (210 cases) , and the imaging characteristics of the two groups were compared.

Results

A total of 323 patients with benign pulmonary nodules diagnosed postoperatively were included in this study. The maximum diameter of the nodules was predominantly less than 20 mm, mostly located in the right upper lobe, and mainly presented as mixed ground-glass nodules. Some nodules exhibited imaging characteristics of malignant nodules, such as irregular shape, blurred borders, lobulation, spiculation, and pleural indentation. The m-CT value of the nodules ranged from –820 to –116.6 (–490.7±156.7) HU. The postoperative pathological types were mainly tuberculoma (73/323) , hamartoma (64/323) , and nonspecific inflammation (59/323) . Compared with the surgical indication benign nodule group, the non-surgical indication benign nodule group had more nodules with diameters less than 10 mm, and the incidences of malignant imaging characteristics such as lobulation, spiculation, and pleural indentation were lower.

Conclusions

Benign pulmonary nodules resected surgically were predominantly mixed ground-glass nodules, with some exhibiting imaging characteristics of malignant nodules. Postoperative pathological types indicated that tuberculoma and hamartoma were the most common benign lesions, followed by nonspecific inflammation. For ground-glass nodules with diameters less than 10 mm, follow-up observation may be considered. The m-CT value may have some application value in predicting the benign or malignant nature of nodules.

Key words: Benign pulmonary nodules, Pulmonary neoplasms, Clinical features, High-resolution computed tomography

Yu Wang, Zekai Zhang, Mingsheng Wu, Gaoxiang Wang, Xiaohui Sun, Jun Wang, Meiqing Xu, Tian Li, Shibin Xu, Mingran Xie. Clinical characteristics of 323 patients with postoperative pathological diagnosis of benign pulmonary nodules[J]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2024, 11(03): 167-174.

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References 40

1	Mazzone PJ，Lam L．Evaluating the Patient With a Pulmonary Nodule: A Review[J]．JAMA，2022，327(3):264-273．
2	Wu Z，Wang F，Cao W，et al．Lung cancer risk prediction models based on pulmonary nodules: A systematic review[J]．Thorac Cancer，2022，13(5):664-677．
3	Tanoue LT，Tanner NT，Gould MK，et al．Lung cancer screening[J]．Am J Respir Crit Care Med，2015，191(1):19-33．
4	Gould MK，Tang T，Liu IL，et al．Recent Trends in the Identification of Incidental Pulmonary Nodules[J]．Am J Respir Crit Care Med，2015，192(10):1208-1214．
5	Jonas DE，Reuland DS，Reddy SM，et al．Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force[J]．JAMA，2021，325(10):971-987．
6	Bach PB，Mirkin JN，Oliver TK，et al．Benefits and harms of CT screening for lung cancer: a systematic review[J]．JAMA，2012，307(22):2418-2429．
7	Ost D，Fein AM，Feinsilver SH．Clinical practice. The solitary pulmonary nodule[J]．N Engl J Med，2003，348(25):2535-2542．
8	Anderson IJ，Davis AM．Incidental Pulmonary Nodules Detected on CT Images[J]．JAMA，2018，320(21):2260-2261．
9	Bueno J，Landeras L，Chung JH．Updated Fleischner Society Guidelines for Managing Incidental Pulmonary Nodules: Common Questions and Challenging Scenarios[J]．Radiographics，2018，38(5):1337-1350．
10	Tanner NT，Aggarwal J，Gould MK，et al．Management of Pulmonary Nodules by Community Pulmonologists: A Multicenter Observational Study[J]．Chest，2015，148(6):1405-1414．
11	Madariaga ML，Lennes IT，Best T，et al．Multidisciplinary selection of pulmonary nodules for surgical resection: Diagnostic results and long-term outcomes[J]．J Thorac Cardiovasc Surg，2020，159(4):1558-1566.e3．
12	Zhang Q，Wu X，Yang H，et al．Advances in the Treatment of Pulmonary Nodules[J]．Respiration，2024，103(3):134-145．
13	Liu A，Wang Z，Yang Y，et al．Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram[J]．Cancer Commun (Lond)，2020，40(1):16-24．
14	Huang W，Deng H，Li Z，et al．Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules[J]．Front Oncol，2023，13:1255007．
15	Xie X，Liu K，Luo K，et al．Value of dual-layer spectral detector computed tomography in the diagnosis of benign/malignant solid solitary pulmonary nodules and establishment of a prediction model[J]．Front Oncol，2023，13:1147479．
16	Zhang R，Tian P，Chen B，et al．Predicting Lung Cancer Risk of Incidental Solid and Subsolid Pulmonary Nodules in Different Sizes[J]．Cancer Manag Res，2020，12:8057-8066．
17	Xiao YD，Lv FJ，Li WJ，et al．Solitary Pulmonary Inflammatory Nodule: CT Features and Pathological Findings[J]．J Inflamm Res，2021，14:2741-2751．
18	中华医学会呼吸病学分会肺癌学组，中国肺癌防治联盟专家组．肺结节诊治中国专家共识(2018年版)[J]．中华结核和呼吸杂志，2018，41(10):763-771．
19	Gould MK，Donington J，Lynch WR，et al．Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines[J]．Chest，2013，143(5 Suppl):e93S-e120S．
20	Reid M，Choi HK，Han X，et al．Development of a Risk Prediction Model to Estimate the Probability of Malignancy in Pulmonary Nodules Being Considered for Biopsy[J]．Chest，2019，156(2):367-375．
21	Callister ME，Baldwin DR，Akram AR，et al．British Thoracic Society guidelines for the investigation and management of pulmonary nodules[J]．Thorax，2015，70 Suppl 2:ii1-ii54．
22	MacMahon H, Naidich DP, Goo JM，et al．Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017[J]．Radiology，2017，284(1):228-243．
23	Doerr F，Giese A，Höpker K，et al．LIONS PREY: A New Logistic Scoring System for the Prediction of Malignant Pulmonary Nodules[J]．Cancers (Basel)，2024，16(4):729．
24	Peters AA，Weinheimer O，von Stackelberg O，et al．Quantitative CT analysis of lung parenchyma to improve malignancy risk estimation in incidental pulmonary nodules[J]．Eur Radiol，2023，33(6):3908-3917．
25	Ma XB，Xu QL，Li N，et al．A decision tree model to distinguish between benign and malignant pulmonary nodules on CT scans[J]．Eur Rev Med Pharmacol Sci，2023，27(12):5692-5699．
26	Ferreira JR Jr，Oliveira MC，de Azevedo-Marques PM．Characterization of Pulmonary Nodules Based on Features of Margin Sharpness and Texture[J]．J Digit Imaging，2018，31(4):451-463．
27	Erdogdu E，Ozkan B，Duman S，et al．Predictors of malignancy in patients with solitary pulmonary nodules undergoing pulmonary resection[J]．Clin Respir J，2022，16(5):361-368．
28	Alpert JB，Lowry CM，Ko JP．Imaging the solitary pulmonary nodule[J]．Clin Chest Med，2015，36(2):161-78, vii．
29	He XQ，Huang XT，Luo TY，et al．The differential computed tomography features between small benign and malignant solid solitary pulmonary nodules with different sizes[J]．Quant Imaging Med Surg，2024，14(2):1348-1358．
30	Kim HJ，Cho JY，Lee YJ，et al．Clinical Significance of Pleural Attachment and Indentation of Subsolid Nodule Lung Cancer[J]．Cancer Res Treat，2019，51(4):1540-1548．
31	Tamura M，Matsumoto I，Saito D，et al．Mean Computed Tomography Value to Predict the Tumor Invasiveness in Clinical Stage IA Lung Cancer[J]．Ann Thorac Surg，2017，104(1):261-266．
32	吴汉然，柳常青，徐美青，等．m-CT值在预测临床Ia期肺癌和癌前病变恶性程度中的应用研究[J]．中国肺癌杂志，2018，21(3):190-196．
33	Tamura M，Matsumoto I，Tanaka Y，et al．Predicting recurrence of non-small cell lung cancer based on mean computed tomography value[J]．J Cardiothorac Surg，2021，16(1):128．
34	Peng M，Peng F，Zhang C，et al．Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)[J]．PLoS One，2015，10(6):e0129206．
35	Youguo Z，Chengye W，Xiaofei C，et al．Analysis of the relevance between computed tomography characterization and pathology of pulmonary ground-glass nodules with different pathology types[J]．Turk Gogus Kalp Damar Cerrahisi Derg，2023，31(1):95-104．
36	Yonemori K，Tateishi U，Uno H，et al．Development and validation of diagnostic prediction model for solitary pulmonary nodules[J]．Respirology，2007，12(6):856-862．
37	Global, regional, and national sex differences in the global burden of tuberculosis by HIV status, 1990-2019: results from the Global Burden of Disease Study 2019[J]．Lancet Infect Dis，2022，22(2):222-241．
38	Bai C，Choi CM，Chu CM，et al．Evaluation of Pulmonary Nodules: Clinical Practice Consensus Guidelines for Asia[J]．Chest，2016，150(4):877-893．
39	Fiorelli A，D’Andrilli A，Carlucci A，et al．Pulmonary Hamartoma Associated With Lung Cancer (PHALC Study): Results of a Multicenter Study[J]．Lung，2021，199(4):369-378．
40	Ulas AB，Aydin Y，Eroglu A．Pulmonary Hamartomas: A Single-Center Analysis of 59 Cases[J]．Eurasian J Med，2022，54(3):270-273．

病理类型	例数（%）
结核肉芽肿	73（22.6）
错构瘤	64（19.8）
非特异性炎症	59（18.3）
非特征性良性病变	48（14.9）
肺实质内淋巴结	23（7.1）
隐球菌感染	21（6.5）
支气管扩张	15（4.6）
硬化性血管瘤	8（2.5）
机化性肺炎	6（1.9）
炎性假瘤	3（0.9）
血管畸形	2（0.6）
神经内分泌肿瘤	1（0.3）
总计	323

病理类型	例数（%）
结核肉芽肿	73（22.6）
错构瘤	64（19.8）
非特异性炎症	59（18.3）
非特征性良性病变	48（14.9）
肺实质内淋巴结	23（7.1）
隐球菌感染	21（6.5）
支气管扩张	15（4.6）
硬化性血管瘤	8（2.5）
机化性肺炎	6（1.9）
炎性假瘤	3（0.9）
血管畸形	2（0.6）
神经内分泌肿瘤	1（0.3）
总计	323

临床资料	例数（%）
性别
男	159（49.2）
女	164（50.8）
年龄
≥60岁	117（36.2）
<60岁	206（63.8）
吸烟史
是	55（17.0）
否	268（83.0）
慢性阻塞性肺疾病
是	35（10.8）
否	288（83.2）
临床症状
无症状	279（86.4）
咳嗽	28（8.7）
胸痛	10（3.1）
咯血	6（1.8）
肿瘤家族史
有	6（1.9）
无	317（98.1）

临床资料	例数（%）
性别
男	159（49.2）
女	164（50.8）
年龄
≥60岁	117（36.2）
<60岁	206（63.8）
吸烟史
是	55（17.0）
否	268（83.0）
慢性阻塞性肺疾病
是	35（10.8）
否	288（83.2）
临床症状
无症状	279（86.4）
咳嗽	28（8.7）
胸痛	10（3.1）
咯血	6（1.8）
肿瘤家族史
有	6（1.9）
无	317（98.1）

影像学特征	例数（%）
结节部位
右上叶	106（32.8）
右中叶	19（5.9）
右下叶	90（27.9）
左上叶	41（12.7）
左下叶	67（20.7）
结节类型
纯磨玻璃结节	55（17.0）
混合性磨玻璃结节	241（74.6）
纯实性结节	27（8.4）
形态
不规则	179（55.4）
圆形或类圆形	144（44.6）
边界
清晰	138（42.7）
模糊	185（57.3）
分叶征
有	81（25.0）
无	242（75.0）
毛刺征
有	90（27.9）
无	233（72.1）
空泡征
有	25（7.8）
无	298（92.2）
血管集束征
有	21（6.6）
无	302（93.4）
钙化
有	15（4.7）
无	308（95.3）
胸膜牵扯征
有	130（43.2）
无	193（59.8）
结节最大径（mm）
≤10	152（47.1）
>10～20	125（38.7）
>20～30	46（14.2）
m-CT值均值（HU）	−490.7±156.7
CTR	0.626±0.33

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